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Tier-1 financial brand, metro Hyderabad, and popular data-science title yield moderate competition.
Core ML/GenAI skills are transferable, but finance domain and productionization experience increase sensitivity.
Explicit 10+ years, required LLM/productionization skills, cloud and leadership make filters highly strict.
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Lead end-to-end delivery of machine learning and Generative AI (GenAI) solutions including problem framing, model development, evaluation, and production deployment.
Define and implement evaluation frameworks and governance for ML/LLM systems, including RAG-based retrieval and agentic applications.
Collaborate cross-functionally with AI/ML engineers, data engineers, and platform teams to operationalize models on cloud platforms (Azure preferred) and mentor data scientists.
10+ years overall professional experience, including 8+ years in data science/ML, with at least 5+ years hands-on Python experience.
Bachelor’s or Master’s in Computer Science, Engineering, Mathematics, or related field.
Practical experience with LLMs/Generative AI (e.g., GPT/BERT models) and model lifecycle from experimentation to production.
Experience with cloud ML platforms, preferably Azure or AWS, including deployment and monitoring.
Experienced leader capable of shaping data science strategy and driving architectural/design decisions for advanced ML and GenAI solutions.
Strong technical background in ML model evaluation, experimentation, and productionization within enterprise cloud environments.
Familiar with RAG methods, agentic application design, and collaborative cross-functional project delivery involving engineering and data teams.